Towards transparent financial AI: a systematic review of graph learning and explainable methods for credit risk and fraud detection
Graph-based learning and explainable artificial intelligence (XAI) are increasingly used to improve both predictive performance and transparency in financial risk modelling. This paper presents a systematic literature review of AI and machine learning approaches for credit risk assessment and fraud detection, with specific attention to graph-based methods and explainable frameworks. Following a PRISMA-guided methodology, 149 studies published between 2015 and 2025 were analysed across multiple a
Record details
Published: 15 July 2026
Source: Artificial Intelligence Review
Category: Research
Topics: Transparency
Retrieved: 16 July 2026
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How to cite this record
ethics.ai (15 July 2026), “Towards transparent financial AI: a systematic review of graph learning and explainable methods for credit risk and fraud detection,” evidence record 10683, https://ethics.ai/record/10683 (originally published by Artificial Intelligence Review).
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